Tuesday, 26 December 2017

Unpaid work

In the past the Census only concerned itself with traditional market based employment. More recently it was widened its scope to include some information on other aspects of employment, notably domestic work and volunteering. I wouldn't want people to think I'm a stick in the mud so here is a little information about those two aspects of Gazette area activity.

Domestic work

This includes work that the person did without pay, in their own home and in other places, for themselves, their family and other people in the household, in the week prior to Census night.I can't remember how I answered the Census question (and it was complicated by us being on a camping trip in Queensland at the time) but would be surprised if a two person household (who mainly eat at home) would put in less than 20 hours on these tasks per week. I'm not sure how much extra time is added by additional people and expect quite a bit would be reduced by eating out (eg lunches at work). The impact of larger households can't be examined as Table Builder doesn't enable tabulation of Person Data with Household data - in this case number of hours of domestic work and size of household.The most common analysis of this variable is to look at the traditional/stereotype of women doing the majority of these duties within the household. That is reflected in this first chart.

I wondered whether the extent of paid employment had an impact on this comparison, so restricted the analysis to full time workers. There is still a difference between the sexes, but as expected having a full time job does reduce the amount of time put in to domestic duties.

I thought it might be interesting to combine the two approaches so the next two charts compare total responses to the domestic question and responses by full time workers for males and females.

To me the outstanding feature of the analysis is the fact that close to 50% of females with a full time job devote 5 -14 hours to domestic work.

Another aspect of stereotyping is that parents do most of the domestic chores while the children are excused such duties. As the Census question is restricted to people aged 15+ that cant'really be shown. However it is possible to look at the way domestic duties change by age of the person. As the hours of domestic work are given in ranges I approximated the actual hours as the mid-point of each range and then calculated the average hours for 10 year age groups.

Bearing in mind the dodgy averaging process this shows a believable picture with hours of domestic work rising in the first two groups and then largely flattening out. To really look at this would require some form of analysis that looked at age, employment status and household size in one go. I have neither the data not the analytic tools to do that.

Volunteering

This item records people who spent time doing unpaid voluntary work through an organisation or group, in the twelve months prior to Census night. It excludes work done:

as part of paid employment

if main reason is to qualify for Government benefit; obtain an educational qualification; or due to a community work order; or

as part of a family business.

Overall 23.3% of people aged 15+ in the Gazette area volunteered. This contrasts with 19.0 people in Australia as a whole: to quote young Mr Grace "You've all done very well." (Or at least 23.3% of you have!)

My first thought was to use a time-budget approach by cross classifying the volunteering rate (ie the % of people in a group who said they did volunteer) by Labour Force Status and sex. I have included people who did not give a response to this question in the total. In effect this is saying that no answer = an answer of "No" and conforms with the well known situation that if a true response makes people feel uncomfortable (eg guilt about not volunteering) they'll leave the question blank.

The most interesting part of this is the contrast between the sexes for the "Other in LF"category. This is effectively unemployed people. I'm not going to try to hypothesis why this is so.

The next approach is to look at the age-specific rates. As it is easy to do I cross-classified by sex.

The extremes are the most interesting with a high proportion of females aged 15 to 19 volunteering and no males aged 80 to 89. Obviously young adults have other things on their minds than volunteering!

Again this could be the subject of much multivariate analysis if I had the resources (and/or knowledge) to do so..